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Hadoop Training in Gurgaon

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  • With this course, you'll learn much more than Hadoop, like Big Data. We will teach you how to install, configure, and handle big data with our course.
  • It will not only explain how these technologies interact, but also show you how to use them to solve real-world business problems! UNIX and Java knowledge are the only prerequisites. The knowledge and confidence you gain from taking this course will benefit your career.
  • This course will prepare you for big data projects right away. In this course, you'll learn about HDFS, MapReduce, Apache Pig, and Hive.
  • EC2 instances and Hadoop instances can be created and configured. The examples, applications, and explanations provided will make all subjects easy to understand by students at any level.
  • It is beneficial for students to attend both theory and practical sessions. Our graduates are ready for jobs with a wide variety of companies after they graduate.
  • This course will show you how to use Hadoop to solve problems in the real world, and you will learn how to implement Hadoop in your daily tasks. Furthermore, you'll receive a valuable certificate of completion once you've completed the course!
  • Concepts: High Availability, Big Data opportunities, Challenges, Hadoop Distributed File System (HDFS), Map Reduce, API discussion, Hive, Hive Services, Hive Shell, Hive Server and Hive Web Interface, SQOOP, H Catalogue, Flume, Oozie.
  • Classroom Batch Training
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Course Objectives

In this hands-on Big Data Hadoop training course, you'll perform real-life, industry-based projects utilizing Integrated Lab. This can be an industry-recognized Hadoop Certification Classes that's a blend of the training courses in Hadoop developer, Hadoop administrator, Hadoop Tester, and analytics utilizing Apache Spark. Our Hadoop certification training course helps you to understand the ideas of the Hadoop framework, preparing you for Certified Associate (CCA) AND HDP Certified Developer (HDPCD). Learn how Hadoop Ecosystem parts fit into the Big Data Analytics Lifecycle.

Hadoop becomes in handy after we check big data. It should not make the process faster but gives us the aptitude to use multiprocessing capacity to manage big data. In short, Hadoop provides us the capability to business the complexities of high volume, velocity, and type of data (popularly referred to as 3Vs).

These days organizations want Hadoop directors to require care of large Hadoop clusters. High firms like Facebook, eBay, Twitter, etc are using Hadoop. The professionals with Hadoop skills are a unit in vast demand. In keeping with Payscale, the typical pay for Hadoop directors is Rs.1,21,000.

  • Since the duty entails learning knowledge, the titles knowledge Scientists, knowledge Engineers, knowledge Analysts, are the duty titles offered to a licensed Hadoop Developer.
  • Jobs are a lot of in-demand across the planet a study by the puts a calculable shortage of a 190,000 data scientists within the North American nation alone.
  • If curious about numbers, do the mathematics and calculate the world figures.
  • Fundamentals of Hadoop and YARN and write applications utilizing them.
  • HDFS, MapReduce, Hive, Pig, Sqoop, Flume, and ZooKeeper.
  • Spark, Spark SQL, Streaming, Data Frame, RDD, GraphX, and MLlib review Spark applications.
  • Running with Avro data formats.
  • Studying real-life projects utilizing Hadoop and Apache Spark.
  • Be provided to make Big Data Hadoop Certification.
However, it's highly advisable if you possess the following skills sets:
  • Mathematical and Analytical expertise.
  • Excellent critical reasoning and problem-solving skills.
  • Technical understanding of Python, R, and SAS tools.
  • Communication skills.
Supporting training in Hadoop and big data is kind of beneficial to the individual through this data-driven world:
  • Improve your career opportunities as more companies work with big data.
  • Specialists with good knowledge and experiences in Hadoop are in need across different industries.
  • Increase your payroll with a brand new skill-set. In line with ZipRecruiter, a Hadoop expert earns a mean of 852,549 INR once a year.
  • Obtain a purchase with leading companies like Google, Microsoft, and Cisco with professions in Hadoop and big data.

Who should take this Hadoop Certification Training Course?

  • Software Developers, Project Managers
  • Software Architects
  • ETL and knowledge deposition Professionals
  • Data Engineers
  • Data Analysts & Business Intelligence Professionals
  • DBAs and decibel professionals

Why should I learn Hadoop to create your career?

On every of the foremost necessary motivating reasons to learn big data Hadoop is that the undeniable fact that it brings an array of opportunities to bolster your career to a new level. As additional and additional firms address big data, they're more and more searching for experts Who will interpret and use knowledge.

How much do Hadoop developers make?

  • Big data engineers will anticipate a 9.3 p.c boost in beginning pay in 2015, with average salaries starting from 1,062,796 INR to 852,549 INR.
  • The typical pay for a Hadoop Developer in the city, CA, is 2,761,333 INR.
  • A Senior Hadoop developer in the city, CA will earn over ₹ 8,91,464 on average.

What are the provisions of a Hadoop training course?

Before trying a Hadoop course, a competitor is usually recommended to own basic data of programming languages like Python, Scala, Java and a far better understanding of SQL and RDBMS.

Is Big Data and Hadoop the same?

Hadoop could be a level framework that may handle the large volume of Big Data and process it, whereas Big Data is just an outsized volume of the data which may be in unstructured and structured data.

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Overview of Hadoop Training in Gurgaon

We offer Big Data Hadoop Training, acknowledged in the industry, which integrates business training, online education, and school training efficiently to meet students educational requirements worldwide. This online Hadoop course allows you to use HDFS and MapReduce to store and analyze large-scale data for more than 10 real-time Big Hadoop data projects. You will obtain a practical understanding of building Apache Spark Scripts for processing data in an efficient way via this online Hadoop Training Course. Register now for the Hadoop course and clear Spark and Hadoop Developer Certification of Certified Associate (CCA). Our Big Data & Hadoop Course in Gurgaon allows you to learn the basics of the Hadoop framework and prepare you for the Hadoop Certification Exam CCA175. Fill the big data processing cycle with how different components of the Hadoop ecosystem fit into it.


Additional Info

Introduction of Big data and Hadoop :

The big info is cited as if the field that treats to investigate and systematically extract information or manage info sets that area unit too large or advanced to treated by ancient process applications package. The huge info is larger and heaps of advanced info sets that's terribly from the new info sources. Info sets area units so voluminous that ancient info processes packages can’t manage them. Forms of vast info area unit PDFs, audios, videos, etc. Hadoop may be a framework that allows the person to first store vast info {in a|during a|in an exceedingly|in a terribly} very disturbing setting, therefore you will technique it parallels. There are unit two components in Hadoop, the first company in HDFS. This allows dumping any quiet info across the cluster. No second half is YARN (processing). This allows the processing of the knowledge that's held on in HDFS. Hadoop is used for – log method, Search info Warehouse, and Video and Image Analysis.

Three key concepts :

volume, variety, and speed. The analysis of big info presents challenges in sampling, then antecedents material possession exclusively observations and sampling. Therefore, vast info sometimes includes info with sizes that exceed the potential of the associate package to technique among an applicable time and worth. Current usage of the term vast info tends to take a seat down with the utilization of revelatory analytics, user behavior analytics, or positive various advanced info analytics methods that extract worth from vast info, and often to a particular size of the information set. "There is little doubt that the amount of information already available is consequently large, but this is not the main feature of this new topic for information. Information sets can be analyzed to see new relationships with "economic developments, forest illnesses, and therefore the fight against crime." In fields such as internet search, fintech, care analytics, geographic information systems, urban, scientists, business executives, doctors, advertising and government confront issues with massive data sets. science, and business science. Scientists encounter limitations in e-Science work, in conjunction with meteorology, genomics, connectors, advanced physics simulations, biology, and environmental analysis.

Roles and Responsibilities Big Data and Hadoop :

  • Check, back-up, and monitor the whole system, routinely
  • Ensure that the property and network are invariably up and running
  • Plan for capability upgrading or retrenchment as and once the necessity arises
  • Manage HDFS and make sure that it's operating optimally the least bit times
  • Secure the Hadoop cluster during a foolproof manner
  • Regulate the administration rights looking on the duty profile of users
  • Add new users over time and discard redundant users swimmingly
  • Take end-to-end responsibility of the Hadoop life cycle within the organization
  • Be the bridge between information Scientists, Engineers, and also the structure desires
  • Do in-depth demand analyses and solely opt for the work platform
  • Acquire full data of Hadoop design and HDFS
  • Have data of the agile methodology for delivering software system solutions
  • Design, develop, document, and designer Hadoop applications
  • Manage and monitor Hadoop log files
  • Develop Map Reduce cryptography that works seamlessly on Hadoop clusters
  • Have operating data of SQL, NoSQL, information storage, and DBA
  • Be Associate in Nursing professional in newer ideas like Apache Spark and Scala programming
  • Acquire complete data of the Hadoop system and Hadoop Common

Required skills for big data and Hadoop

1. Apache Hadoop :

There has been tremendous growth within the development of Apache Hadoop within a previous couple of years. Hadoop's elements like Hive, Pig, HDFS, HBase, Map Reduce, etc. square measure in high demand currently. Hadoop has entered its second decade currently however has mature in quality from the last 3-4 years. some software system firms square measure exploitation Hadoop clusters ordinarily. This can be beyond question the massive factor in big knowledge. The aspiring professionals shall become good during this technology.

2. NoSQL :

The NoSQL databases as well as Couch base, MongoDB, etc. square measure exchange the standard SQL databases like DB2, Oracle, etc. These distributed NoSQL knowledge bases facilitate meeting the large data storage and access wants. This enhances the experience of Hadoop with its knowledge crunching ability. The professionals with NoSQL experience will notice opportunities everyplace.

3. Knowledge Visualization :

The info visualization tools like QlikView, Tableau will facilitate in understanding the analysis performed by the analytics tools. The advanced massive knowledge technologies and processes dole out square measure robust to know, and this can be wherever the role of pros inherits the image. Knowledgeable well versed with knowledge visualization tools will get an opportunity to grow in their career with large organizations.

4. Machine Learning :

Data processing and Machine Learning square measure the 2 hot fields of massive knowledge. The landscape of massive knowledge is immense, these 2 create a crucial contribution to the sector. The professionals that may use machine learning for closing prognostication and prescriptive analysis square measure scarce. These fields will facilitate in developing a recommendation, classification, and personalization systems. The professionals with the information of information mining and machine learning square measure heavily paid yet.

Tools of Big data and Hadoop :

  • HDFS :

    Hadoop Distributed classification system, that is usually called HDFS is intended to store an outsized quantity of knowledge, this is kind of tons a lot of economical than the NTFS (New kind classification system) and FAT32 File System, that are employed in Windows PCs. HDFS is employed to cater giant chunks of knowledge quickly to applications. Yahoo has been exploitation the Hadoop Distributed classification system to manage over forty petabytes of knowledge.

  • HIVE :

    Apache, which is usually acknowledged for hosting servers, has gotten their resolution for Hadoop’s information as Apache HIVE knowledge warehouse computer code. This makes it simple for the US to question and manage giant datasets. With HIVE, all the unstructured knowledge is projected with a structure, and later, we will question the info with SQL like language called HiveQL. HIVE provides completely different storage sorts like plain text, RCFile, Hbase, ORC, etc. HIVE conjointly comes with intrinsical functions for the users, which may be wont to manipulate dates, strings, numbers, alternative, and several other varieties of data processing functions.

  • NoSQL :

    Structured question Languages are in use for a protracted time, currently because the knowledge is generally unstructured, we tend to need a question Language that doesn’t have any structure. this can be resolved in the main through NoSQL. we've got primarily key combined values with secondary indexes. NoSQL will simply be integrated with Oracle information, Oracle billfold, and Hadoop. This makes NoSQL one in all the wide supported Unstructured source languages.

  • Mahout :

    Apache has conjointly developed its library of various machine learning algorithms that are thought of as the driver. the driver is enforced on prime of Apache Hadoop and uses the MapReduce paradigm of BigData. As we tend to all comprehend the Machines learning various things daily by generating knowledge supported by the inputs of a distinct user, this can be called Machine learning and is one of all the essential elements of computing. Machine Learning is commonly wont to improve the performance of any explicit system, and this majorly works on the result of the previous run of the machine.

  • Avro :

    With this tool, we quickly get representations of complicated knowledge structures that are generated by Hadoop’s MapReduce rule. Avro knowledge tool will simply take each input and output from a MapReduce job, wherever it also can format a similar in an exceedingly abundant easier means. With Avro, we will have period categorization, with simply apprehensible XML Configurations for the tool.

Features of Big Data and Hadoop :

1. Brings Flexibility In information Processing :

One of the largest challenges organizations have had therein past was the challenge of handling unstructured information. Let’s face it, solely two-hundredth of information in any organization is structured whereas the remainder is all unstructured whose price has been for the most part unnoticed thanks to lack of technology to investigate it. Hadoop manages information whether structured or unstructured, encoded or formatted, or the other sort of information. Hadoop brings the worth to the table wherever unstructured information may help decide the process.

2. Is Easily scalable :

This is a large feature of Hadoop. It's AN open supply platform and runs on industry-standard hardware. That creates Hadoop's extraordinarily scalable platform wherever new nodes may be simply added within the system as and information volume of process desires grows while not sterilization something within the existing systems or programs.

3. Is Fault Tolerant :

In Hadoop, the information is kept in HDFS wherever data mechanically gets replicated at 2 alternative locations. So, even though one or 2 of the systems collapse, the file continues to be obtainable on the third system a minimum of. The extent of replication is configurable and this makes Hadoop an implausibly reliable information storage system. This means, even though a node gets lost or goes out of service, the system mechanically reallocates work to a different location of the info and continues the process.

4. Is nice At quicker processing :

While ancient ETL and batch processes will take hours, days, or maybe weeks to load giant amounts of information, the requirement to investigate that information in the period is changing into the essential day when a day. Hadoop is extraordinarily smart at high-volume execution thanks to its ability to try multiprocessing. Hadoop will perform batch processes ten times quicker than on one thread server or the mainframe.

5. Ecosystem Is Robust :

Hadoop includes a sturdy scheme that's like-minded to fulfill the analytical desires of developers and tiny to massive organizations. Hadoop scheme comes with a collection of tools and technologies creating an awfully a lot of appropriate to deliver to a spread of knowledge process desires. Just to call a couple of, Hadoop scheme comes with comes like MapReduce, Hive, HBase, Zookeeper, HCatalog, Apache Pig, etc. and plenty of new tools and technologies are being else to the scheme because the market grows.

6. Hadoop is extremely value Effective :

Hadoop generates value edges by transportation massively parallel computing to goods servers, leading to a considerable reduction within the value per TB of storage, which successively makes it affordable to model all of your information. Apache Hadoop was developed to assist Internet-based firms to handle prodigious volumes of knowledge, consistent with some analysts.

Integration Module of Big Data and Hadoop :

  • The speedy emergence of Hadoop is driving a paradigm shift in however organizations ingest, manage, transform, store and analyze massive information. Deeper analytics, larger insights, new products and services, and better service levels square measure all attainable through this technology, facultative you to cut back prices considerably and generate new revenues. massive information and Hadoop come to rely on assembling, moving, reworking, cleansing, integrating, governing, exploring, and analyzing huge volumes of various forms of information from many alternative sources.

  • Accomplishing all this needs a resilient, finish-to-finish info integration answer that's massively climbable and provides the infrastructure, capabilities, processes, and discipline needed to support Hadoop comes. an efficient massive information integration answer delivers simplicity, speed, measurability, practicality, and governance to supply expendable information from the Hadoop swamp. while not effective integration, you get “garbage in, garbage out”—not a decent instruction for trusty information, abundant less correct and complete insights, or transformative results.

Certification of Big Data and Hadoop :

The large information Hadoop certification employment is meant to convey to you Associate in Nursing in-depth data of the big information framework exploitation Hadoop and Spark. throughout this active Hadoop course, you will execute real-life, industry-based comes exploitation Integrated work. large information Hadoop certification employment on-line course is best fitted thereto, Information Management, and Analytics professionals attempting to realize expertise in large information Hadoop, in conjunction with package Developers and designers, Senior IT professionals, Testing and Mainframe professionals, Business Intelligence professionals, Project Managers, Aspiring information Scientists, Graduates attempting to begin a career in large information Analytics. Professionals entering into large information Hadoop certification employment have to be compelled to have a basic understanding of Core Java and SQL. If you'd prefer to brush up your Core Java skills, easy learn offers a complimentary self-paced course Java wants for Hadoop as a neighborhood of the course program.

Payscale for Big Data and Hadoop :

Hence, in an exceedingly non-marginal role, BigData and Hadoop Developer an average remuneration is concerning 8.5lacs. Moreover, a manager will earn up to 15Lcas. This remuneration varies from skill to skills. If an individual is competent then they need a better pay scale and that they might get a hike in their salaries.

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Key Features

ACTE Gurgaon offers Hadoop Training in more than 27+ branches with expert trainers. Here are the key features,
  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.


Syllabus of Hadoop Course in Gurgaon
Module 1: Introduction to Hadoop
  • High Availability
  • Scaling
  • Advantages and Challenges
Module 2: Introduction to Big Data
  • What is Big data
  • Big Data opportunities,Challenges
  • Characteristics of Big data
Module 3: Introduction to Hadoop
  • Hadoop Distributed File System
  • Comparing Hadoop & SQL
  • Industries using Hadoop
  • Data Locality
  • Hadoop Architecture
  • Map Reduce & HDFS
  • Using the Hadoop single node image (Clone)
Module 4: Hadoop Distributed File System (HDFS)
  • HDFS Design & Concepts
  • Blocks, Name nodes and Data nodes
  • HDFS High-Availability and HDFS Federation
  • Hadoop DFS The Command-Line Interface
  • Basic File System Operations
  • Anatomy of File Read,File Write
  • Block Placement Policy and Modes
  • More detailed explanation about Configuration files
  • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
  • How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
  • FSCK Utility. (Block report)
  • How to override default configuration at system level and Programming level
  • HDFS Federation
  • ZOOKEEPER Leader Election Algorithm
  • Exercise and small use case on HDFS
Module 5: Map Reduce
  • Map Reduce Functional Programming Basics
  • Map and Reduce Basics
  • How Map Reduce Works
  • Anatomy of a Map Reduce Job Run
  • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
  • Job Completion, Failures
  • Shuffling and Sorting
  • Splits, Record reader, Partition, Types of partitions & Combiner
  • Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
  • Types of Schedulers and Counters
  • Comparisons between Old and New API at code and Architecture Level
  • Getting the data from RDBMS into HDFS using Custom data types
  • Distributed Cache and Hadoop Streaming (Python, Ruby and R)
  • YARN
  • Sequential Files and Map Files
  • Enabling Compression Codec’s
  • Map side Join with distributed Cache
  • Types of I/O Formats: Multiple outputs, NLINEinputformat
  • Handling small files using CombineFileInputFormat
Module 6: Map Reduce Programming – Java Programming
  • Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
  • Sorting files using Hadoop Configuration API discussion
  • Emulating “grep” for searching inside a file in Hadoop
  • DBInput Format
  • Job Dependency API discussion
  • Input Format API discussion,Split API discussion
  • Custom Data type creation in Hadoop
Module 7: NOSQL
  • ACID in RDBMS and BASE in NoSQL
  • CAP Theorem and Types of Consistency
  • Types of NoSQL Databases in detail
  • Columnar Databases in Detail (HBASE and CASSANDRA)
  • TTL, Bloom Filters and Compensation
<strongclass="streight-line-text"> Module 8: HBase
  • HBase Installation, Concepts
  • HBase Data Model and Comparison between RDBMS and NOSQL
  • Master & Region Servers
  • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
  • Catalog Tables
  • Block Cache and sharding
  • DATA Modeling (Sequential, Salted, Promoted and Random Keys)
  • Java API’s and Rest Interface
  • Client Side Buffering and Process 1 million records using Client side Buffering
  • HBase Counters
  • Enabling Replication and HBase RAW Scans
  • HBase Filters
  • Bulk Loading and Co processors (Endpoints and Observers with programs)
  • Real world use case consisting of HDFS,MR and HBASE
Module 9: Hive
  • Hive Installation, Introduction and Architecture
  • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
  • Meta store, Hive QL
  • OLTP vs. OLAP
  • Working with Tables
  • Primitive data types and complex data types
  • Working with Partitions
  • User Defined Functions
  • Hive Bucketed Tables and Sampling
  • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
  • Dynamic Partition
  • Differences between ORDER BY, DISTRIBUTE BY and SORT BY
  • Bucketing and Sorted Bucketing with Dynamic partition
  • RC File
  • Compression on hive tables and Migrating Hive tables
  • Dynamic substation of Hive and Different ways of running Hive
  • How to enable Update in HIVE
  • Log Analysis on Hive
  • Access HBASE tables using Hive
  • Hands on Exercises
Module 10: Pig
  • Pig Installation
  • Execution Types
  • Grunt Shell
  • Pig Latin
  • Data Processing
  • Schema on read
  • Primitive data types and complex data types
  • Tuple schema, BAG Schema and MAP Schema
  • Loading and Storing
  • Filtering, Grouping and Joining
  • Debugging commands (Illustrate and Explain)
  • Validations,Type casting in PIG
  • Working with Functions
  • User Defined Functions
  • Types of JOINS in pig and Replicated Join in detail
  • SPLITS and Multiquery execution
  • Error Handling, FLATTEN and ORDER BY
  • Parameter Substitution
  • Nested For Each
  • User Defined Functions, Dynamic Invokers and Macros
  • How to access HBASE using PIG, Load and Write JSON DATA using PIG
  • Piggy Bank
  • Hands on Exercises
Module 11: SQOOP
  • Sqoop Installation
  • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism, All tables Import)
  • Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE
  • Hands on Exercises
Module 12: HCatalog
  • HCatalog Installation
  • Introduction to HCatalog
  • About Hcatalog with PIG,HIVE and MR
  • Hands on Exercises
Module 13: Flume
  • Flume Installation
  • Introduction to Flume
  • Flume Agents: Sources, Channels and Sinks
  • Log User information using Java program in to HDFS using LOG4J and Avro Source, Tail Source
  • Log User information using Java program in to HBASE using LOG4J and Avro Source, Tail Source
  • Flume Commands
  • Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG
Module 14: More Ecosystems
  • HUE.(Hortonworks and Cloudera)
Module 15: Oozie
  • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
  • Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
  • Zoo Keeper
  • HBASE Integration with HIVE and PIG
  • Phoenix
  • Proof of concept (POC)
Module 16: SPARK
  • Spark Overview
  • Linking with Spark, Initializing Spark
  • Using the Shell
  • Resilient Distributed Datasets (RDDs)
  • Parallelized Collections
  • External Datasets
  • RDD Operations
  • Basics, Passing Functions to Spark
  • Working with Key-Value Pairs
  • Transformations
  • Actions
  • RDD Persistence
  • Which Storage Level to Choose?
  • Removing Data
  • Shared Variables
  • Broadcast Variables
  • Accumulators
  • Deploying to a Cluster
  • Unit Testing
  • Migrating from pre-1.0 Versions of Spark
  • Where to Go from Here
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Hands-on Real Time Hadoop Projects

Project 1
Real-time Tracking of Vehicles Project

The system allows users to locate their vehicles anytime and anywhere. Also, it can replay a past trace of the vehicle's route history.

Project 2
Analysis of Network Traffic Project

Traffic analysis is the process of intercepting and examining messages in order to deduce information from patterns in communication, which can be performed.

Project 3
Road Lane Line Detection Project

The system has an objective to identify the lane marks. The algorithm followed in this paper is to detect lane markings on the road by giving the video of the road as an input.

Project 4
Sentiment Analysis Project

Objective Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion and procedure by which information is extracted.

Our Engaging Placement Partners

ACTE Gurgaon for affirmation and Guaranteed Situations. Our Work Situated classes are educated by experienced confirmed experts with broad certifiable experience. All our Best around down to earth than hypothesis model.
  • Our applicants will be given compulsory day by day, week by week, and month to month appraisals so they can be evaluated by us.
  • We make guarantee that ability and enlistment stay associated by defining course modules that are as per the business' prerequisites and requests.
  • Our free help with continue composing guarantees that our learners get a lot more enrollment specialist sees and will draw them nearer to getting their fantasy occupations.
  • For this, we furnish our applicants with our notes and give them legitimate itemized preparing, and direct tests also.
  • We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
  • Our applicants will be needed to finish day by day, week by week, and month to month assessments with the end goal for us to assess them.

Get Certified By MapR Certified Hadoop Developer (MCHD) & Industry Recognized ACTE Certificate

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees. Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

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About Skillful Hadoop Instructor

  • Our Big Data and Hadoop Training in Gurgaon have Coach's experience will assist our learners with acquiring the certainty and abilities they should be a corporate achievement.
  • Our coaches are roused by the up-degree of their current abilities and have happy declaration.
  • Tutors experience will assist our learners with acquiring the certainty and abilities they should be a corporate achievement.
  • We have guaranteed Big Data and Hadoop Training mentors who offer their direction and backing to our learners to help them in accomplishing their fantasy occupations.
  • Upgrading their current capacities propels our coaches, and they have an inspirational perspective. Their specific capacities help with distinguishing the requirement for viable.
  • Trainers among members, and they are devoted to giving the most significant level of learning and advancement that guarantees a decent encounter.

Hadoop Course Reviews

Our ACTE Gurgaon Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.



"I would like to recommend to the learners who wants to be an expert on Big Data just one place i.e.,ACTE institute at Anna nagar. After several research with several Training Institutes I ended up with ACTE. My Big Data Hadoop trainer was so helpful in replying, solving the issues and Explanations are clean, clear, easy to understand the concepts and it is one of the Best Training Institute for Hadoop Training"

Andrews Jhon

Software Engineer

Hadoop Classes are conducting by real time experience faculty in ACTE. This institute provides a very deepest explanation in teaching for any setups and end to end cycles. Helping in real time scenarios if we face any when and then. Communication also good, any one can understand the functionality in Gurgaon. Definatly worthfull.


Software Engineer

The training here is very well structured and is very much peculiar with the current industry standards. Working on real-time projects & case studies will help us build hands-on experience which we can avail at this institute. Also, the faculty here helps to build knowledge of interview questions & conducts repetitive mock interviews which will help in building immense confidence. Overall it was a very good experience in availing training in Tambaram at the ACTE Institute. I strongly recommend this institute to others for excelling in their career profession.



I had an outstanding experience in learning Hadoop from ACTE Institute. The trainer here was very much focused on enhancing knowledge of both theoretical & as well as practical concepts among the students. They had also focused on mock interviews & test assignments which helped me towards boosting my confidence.


Software Engineer

The Hadoop Training by sundhar sir Velachery branch was great. The course was detailed and covered all the required knowledge essential for Big Data Hadoop. The time mentioned was strictly met and without missing any milestone.Should be recommended who is looking Hadoop training course ACTE institute in Chennai.

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  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    • Gives
    • For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Hadoop training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Hadoop Course At ACTE?

  • Hadoop Course in ACTE is designed & conducted by Hadoop experts with 10+ years of experience in the Hadoop domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Hadoop batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Hadoop. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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